1. Field of the Invention
The present invention relates to computer software for business management and, more specifically, to a computer implemented method for estimating stock levels in production-distribution networks with inventory control.
2. Description of Prior Art
The manufacturing of computers, consumer electronics, or high-technology electronic devices are growing industries with rapidly changing production processes that require multiple stockholding points. One of the great challenges in such an environment is a company's ability to meet end-customer demand while facing demand and technology uncertainties.
If inventories are managed successfully, rewards can be tremendous. However, the penalty for keeping too little stock goes beyond the cost of foregone revenue. It includes lost potential for additional business, loss of future design gains, and a drop of pricing leverage in the marketplace. The penalty for keeping too much stock includes opportunity cost of financing additional inventory and severely reduced profit margins caused by rapidly declining prices in the technology market.
A production-distribution network consists of a collection of manufacturing sites, warehouses, distribution centers, and retailers through which products flow on their way from manufacturer to the final customer. The key management challenge that high-technology industries are facing is to determine where and in what quantities to hold safety stock in the network so as to protect against uncertainties, and to ensure that target customer service levels are met. Aggressive service level targets require significant inventory planning, given the mix of build-to-stock and build-to-order products reflected in most company's portfolios. Such inventories are subject to high-countervailing costs and to overall inventory budget constraints. Today, the determination of inventory levels is localized and often ad hoc, and not based on an analysis of optimal levels and deployment. As a result, the business impact, in terms of the trade-off between inventory investment and customer serviceability or delinquency, is far from being well understood.
Determining the optimal values of inventory levels in multi-stage production-distribution networks is extremely difficult, and few real-world inventory management systems have the capability to accurately predict target stock levels. The difficulty of the problem arises from the fact that the quantity of safety stock held at one stocking location, and the policy determining replenishment of inventory at that location, will affect other stockholding locations in the network. Management systems are needed that have the capability to accurately represent the interdependencies of all links in a production-distribution network, and that allow planners to quantify the impact of decisions on inventory management at one location on other participants in the network.
Computational methods that address the problem of how to allocate safety stock in a production-distribution network are largely unavailable, although some effort has been expended into obtaining quantitative performance models for such systems.
H. Lee and C. Billington in "Material Management in Decentralized Supply Chains," Operations Research, 41, 835-847, 1993, develop an approximate method to estimate the performance of production-distribution networks with base-stock controls. A simulation-based approach to obtain gradient information with respect to base-stock levels in a multi-stage production-distribution system is discussed by P. Glasserman and S. Tayur in "Sensitivity Analysis of Base-stock Levels in Multiechelon Production-inventory Systems," Management Science, 41, 263-281, 1993.
A method to quantitatively assess inventory-service level tradeoffs in production-distribution networks with base-stock control is described in commonly owned, co-pending U.S. patent application Ser. No. 08/625,455, which is herewith incorporated by reference. The method captures the interdependence of safety stock levels at different stocking locations as well as their effect on overall system performance. It is to be used for both performance evaluation and optimization. In the former case, the user specifies the base-stock level for every stocking location in the network, and the method estimates end-customer service levels and the average dollar value of inventory held in the network. In the case of optimization, a constrained non-linear optimization problem is formulated which minimizes the average total dollar value of inventory in the network, subject to supporting desired customer service level targets. The optimization is carried out using a software package implementing a conjugate gradient search method. Additionally, U.S. patent application Ser. No. 08/625,455 describes a performance evaluation method.
For descriptions of the base-stock control policy as well as examples of how it is used, refer to E. A. Silver and R. Peterson, "Decision Systems for Inventory Management and Production Planning," Wiley, New York 2nd. Ed., 1985; W. J. Hopp and M. L. Spearman, "Factory Physics," Irwin, 1996; and R. J. Tersine, "Principles of Inventory and Materials Management," Prentice Hall, Englewood Cliffs, 4th. Ed., 1994. Descriptions and examples of other decentralized inventory control systems can be found in J. A. Buzacott and J. G. Shanthikumar, "Stochastic Models of Manufacturing Systems," Prentice Hall, Englewood Cliffs, 1993.
What is needed is a system for providing a general framework for inventory management in production-distribution networks in the presence of constrained capital budgets which possesses the following features:
1. it can be implemented in conjunction with any given inventory control policy; PA1 2. the framework supports the use of simulation-based or analytical methods to evaluate the performance of a given production-distribution network; PA1 3. it does not require dedicated software to carry out the optimization process; and PA1 4. it allows to factor real-world requirements such as inventory budget constraints, projected dollar delinquencies, or pre-defined product stockholding levels in its calculations.